To close a wound, or during a surgery, a doctor or nurse may need to tie a knot to complete a suture. Typically, a standard array of knots is used to close a suture, and a doctor or nurse would learn some or all of these knots in school or training. Part of the training process may include supervision by a trained doctor or nurse who may watch the trainee tie the knot, and may examine the completed knot to ensure that the correct knot type was used, and that the knot was tied correctly. When the knot is tied using string, and the trainer is available to watch the trainee tie the knot, it is relatively straightforward for the trainer to recognize the knot used. However, knot detection by a computer is significantly more difficult.
Knot detection, in general, is an NP-complete problem, which means that it takes an exponential amount of time, computationally, to recognize a knot based on the knot presented. The use of general-purpose knot-detection algorithms in a simulation tool may impair the speed and effectiveness of the simulation tool as a training device, as they require a significant amount of time to execute. Existing knot detection algorithms also impose constraints on the definition of knots input into the algorithm that may render those algorithms less desirable for use in a simulation system.